Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on...

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Autores principales:	Safa A. Al-Naimi, Salih A.J. Salih, Hayder A. Mohsin
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2017
Materias:	slurry bubble column reactor mass transfer coefficient neural network Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/05a384066a7548588d6260ccfa030d2f
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spelling	oai:doaj.org-article:05a384066a7548588d6260ccfa030d2f2021-12-02T06:16:27ZSimulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network1818-11712312-0789https://doaj.org/article/05a384066a7548588d6260ccfa030d2f2017-12-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/159https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease with increasing solid concentration. From the experimental work 1575 data points for three systems, were collected and used to predicate kLa. Using SPSS 17 software, predicting of overall volumetric mass-transfer coefficient (kLa) was carried out and an output of 0.05264 sum of square error was obtained for trained data and 0.01064 for test data. Safa A. Al-NaimiSalih A.J. SalihHayder A. MohsinAl-Khwarizmi College of Engineering – University of Baghdadarticleslurry bubble column reactormass transfer coefficientneural networkChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 9, Iss 1 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	slurry bubble column reactor mass transfer coefficient neural network Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	slurry bubble column reactor mass transfer coefficient neural network Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Safa A. Al-Naimi Salih A.J. Salih Hayder A. Mohsin Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
description	The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease with increasing solid concentration. From the experimental work 1575 data points for three systems, were collected and used to predicate kLa. Using SPSS 17 software, predicting of overall volumetric mass-transfer coefficient (kLa) was carried out and an output of 0.05264 sum of square error was obtained for trained data and 0.01064 for test data.
format	article
author	Safa A. Al-Naimi Salih A.J. Salih Hayder A. Mohsin
author_facet	Safa A. Al-Naimi Salih A.J. Salih Hayder A. Mohsin
author_sort	Safa A. Al-Naimi
title	Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
title_short	Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
title_full	Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
title_fullStr	Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
title_full_unstemmed	Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
title_sort	simulation study of mass transfer coefficient in slurry bubble column reactor using neural network
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2017
url	https://doaj.org/article/05a384066a7548588d6260ccfa030d2f
work_keys_str_mv	AT safaaalnaimi simulationstudyofmasstransfercoefficientinslurrybubblecolumnreactorusingneuralnetwork AT salihajsalih simulationstudyofmasstransfercoefficientinslurrybubblecolumnreactorusingneuralnetwork AT hayderamohsin simulationstudyofmasstransfercoefficientinslurrybubblecolumnreactorusingneuralnetwork
_version_	1718399973611012096

Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network

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